Event Searching

ABSTRACT

Events can be searched by identifying a query that includes a time interval and a search component, determining a time increment associated with the time interval, and partitioning the time interval into partitions based on the time increment. For each partition, a relevance of each event in a collection of events that occur at a time in the partition is determined based on the query. A pre-determined number of the relevant events are displayed.

TECHNICAL FIELD

This disclosure relates to event searching.

BACKGROUND

Searchable information may include descriptions of events. An “event”can be an occurrence of certain activity or conduct at a certain timeand place. For example, events can include artistic performances,informational lectures, auctions, opportunities to meet an individual,private social gatherings, etc. Often, events are described in advanceof their occurrence, for example by a promoter or host of the event, anews source, or another person.

SUMMARY

In general, in one aspect: identifying a query, the query including atime interval and a search component; determining a time incrementassociated with the time interval; partitioning, based on the timeincrement, the time interval into partitions; for each partition,determining, based on the query, a relevance of each event in acollection of events, all of which occur at a time in the partition; anddisplaying a pre-determined number of the relevant events.

Implementations may include one or more of the following features:Determining a time increment includes determining a time increment basedon the query. Determining the relevance of each event is based on thesearch component of the query. The query also includes a place componentthat describes a place, and for each partition, and the collection ofevents includes events that occur within a pre-determined relationshipwith the place. The pre-determined relationship includes a geographicalproximity. Determining the relevance of an event includes determining anumerical relevance of the event. Also including generating the query.The query is randomly generated. The search component of the query israndomly generated. The query is generated based on a property of auser. The property includes a query-history of the user. The searchcomponent of the query is generated based on the query-history of theuser. The search component of the query is supplied by a user, and thetime interval of the query is automatically generated. Also includingsuccessively generating two queries, each of which having the samesearch component supplied by the user.

In general, in another aspect: identifying an event described by anelectronic document, wherein identifying the event includes identifyinga time or times at which the event occurs, a place or places at whichthe event occurs, and content from the electronic document, the contentdescribing the event; and recording the time or times at which the eventoccurs, the place or places at which the event occurs, and the contentdescribing the event on a computer readable medium.

Implementations may include one or more of the following features. Alsoincluding identifying the electronic document by using a crawler on acomputer network. The computer network includes a world wide web. Theelectronic document is expressed in a structured language, and the eventis identified using a structure of the language. The structured languageincludes extensible markup language, and the event is identified usingtags in the structured language. The electronic document describes acalendar, and the event includes an invent in the calendar. The event isidentified from a syndicated feed. The syndicated feed includes an RSSfeed. Also including determining a relevance of the event with respectto a pre-determined query, the query being determined prior toidentifying the event.

In general, in another aspect: identifying a query, the query includinga time interval and a search component; identifying one or morepartitions based on the time interval; for each partition, determiningevents based on the search component; and displaying the events for eachpartition.

Implementations may include one or more of the following features. Thequery also includes a place component that describes a place, and foreach partition, and the collection of events includes events that occurwithin a pre-determined relationship with the place. The pre-determinedrelationship includes a geographical proximity. Also includinggenerating the query. The query is randomly generated. The searchcomponent of the query is randomly generated. The query is generatedbased on a property of a user. The property includes a query-history ofthe user. The search component of the query is generated based on thequery-history of the user. The search component of the query is suppliedby a user, and the time interval of the query is automaticallygenerated. Also including successively generating two queries, each ofwhich having the same search component supplied by the user.

Other aspects include other combinations of the features recited aboveand other features, expressed as methods, apparatus, systems,computer-readable media, program products, and in other ways. Otherfeatures and advantages will be apparent from the description and fromthe claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic depiction of an exemplary event search system.

FIG. 2 is a schematic depiction of an exemplary query.

FIG. 3 is a schematic depiction of an exemplary event search engine.

FIG. 4 is a flowchart for populating the event data.

FIG. 5 is a flowchart for identifying which events from a collection ofevents meet a query.

FIG. 6A is an exemplary set of event data.

FIGS. 6B and 6C are schematic depictions of output from the event searchsystem.

FIGS. 7A-D are exemplary outputs from the event search system.

FIG. 8 is a block diagram of a computing device 80 that may be used toimplement the event search system, as either a client or as a server orplurality of servers.

DETAILED DESCRIPTION

Many types of events are described electronically and available forsearching over a computer network, such as the world wide web. Whensearching for events, one is often interested in events that occurduring a given time interval or in a given place. Using traditionalsearch techniques, it can sometimes be cumbersome to identify events ofinterest that are occurring in the desired time or place. For example,if one were to search for musical performances of the band Chicago nearthe city of Boston using some traditional search techniques, the searchresults may include musical performances of the band Boston near thecity Chicago.

Moreover, even if search results describe events that all occur in thespecified location, one is sometimes interested in seeing events thatoccur at times that are spread out across a time interval. For example,if one is interested in events that take place at a local venuethroughout the week, search results about a popular event that occurs onSaturday night may be numerous, while search results about a lesspopular event that occurs on Wednesday afternoon may be less numerous.In such a situation, one may have to examine several search resultsabout the popular event before finding search results about the lesspopular event. This can be time consuming.

Among other things, the techniques described below help find eventsoccurring within a specified time interval in a specified location.

FIG. 1 is a schematic depiction of an exemplary event search system 10.The event search system 10 can accommodate one or more (e.g., several)users 12. Each user 12 is in data communication with the event searchsystem 10. The data communication may be implemented in any way, forexample wirelessly, over a network, by direct physical connection usingmetallic wire or fiber optic cable, etc. The event search system 10includes user data 14, event data 16, and an event search engine 17.

A user 12 can (but need not) register with the event search system 10.If the user 12 registers, the user 12 provides the event search system10 with information, for example a username, a password, a defaultlanguage or geographic location, etc. Moreover, the event search system10 may determine other information about the user 12, which may also bestored as user data 14. For example, the event search system 10 maydetermine the user's current geographic location based on an internetprotocol (“IP”) address of the user 12, etc.

The event data 16 includes descriptions of one or more (e.g., several)events 18. In one implementation, each event 18 includes timeinformation 20, place information 22, and content 24. The timeinformation 20 includes information pertinent to the time at which theevent occurs. In some implementations, the time information 20 caninclude a starting time for an associated event 18, an ending time forthe event 18, or a duration of the event 18. As used herein, the terms“starting time” and “ending time” refer to uniquely specified moments.In particular, specifying a “starting time” or “ending time” should beunderstood to also include specifying a starting or ending day, month,year, etc. The events 18 described by the event data 16 need not occurin any specified relation to any particular moment of time. Inparticular, at any particular moment, the event data 16 may describeevents 18 that have already occurred, are presently occurring, or willoccur in the future.

The place information 22 includes information pertinent to the place atwhich the event occurs. In some implementations, the place information20 can include a description of a geographic location or region, such asa street address, global coordinates (e.g., latitude and longitude), apopular name of a geographic location or region (such as “The Alamo”), aspecified displacement from another geographic location, etc. In someimplementations, the place information 20 can refer to or include an IPaddress of a computer, a uniform resource locator (“URL”), a computername on a network, etc (e.g., when the event is a broadcast event overthe Internet). In some implementations, place information 22 canidentify a broadcast medium or a broadcast source for the event 18.

The content 24 can include description of the nature of the event 18.For example, the content 24 of a barbeque competition event 18 mayinclude a list of participants, a list of prizes, a list of musicalperformances to occur at the competition, rules of the competition,entry fees, etc. The content 24 need not be limited to text. In someimplementations, for example, the content 24 may include graphic, video,audio, or other non-textual information. In some implementations, thecontent 24 may include internal structure. For example, the content 24may specify particular information about the event 18 (for example, anevent title, an event host, an event type, etc.) in metadata orstructured fields within the content 24.

FIG. 2 is a schematic depiction of an exemplary query 26. The query 26includes a time component 28, a place component 30, and a searchcomponent 32. The time component 28 includes a description of a timeinterval. In some implementations, the time component 28 also includesone or more (e.g., several) increments into which the time interval ispartitioned, or into which partitions are further partitioned. Forexample, the time interval may be one week, a time increment may be oneday, and a second time increment may be one hour. The place component 30includes an at least partial description of a place, for example ageographic location, etc. The search component 32 can include anyinformation, such as one or more (e.g., several) search terms. Thoughreference is made to a query 26 that includes all three components28-32, not all are required. Lesser numbers and different components arepossible.

FIG. 3 is a schematic depiction of an exemplary event search engine 17.The event search engine 17 includes a query tool 34, a relevancy tool36, a user data tool 38, an event tool 40, a query generator tool 42,and a display tool 44.

The query tool 34 is operable to gather information based on the query26 and route the information among other components 36-44 of the eventsearch engine 17. In some implementations, the query tool 34 can:retrieve events 18 from the event data 16 that occur within the timeinterval specified in the time component 28 of the query 26; retrieveevents 18 from the event data 16 that occur within the place specifiedin the place component 30 of the query 26; and pass these events 18 tothe relevancy tool 36. In some implementations, the query tool 34 canroute the query 26 to the user data tool 38. This may occur, forexample, if the query 26 is specified by the user 12, and the user 12does not specify a place component 30.

In some implementations, the query tool 34 is configured tohierarchically recognize places, so that when a specific place (e.g.,The Alamo) is within another more general place (e.g., San Antonio,Tex.), both places are recognized as relevant to a query 26 specifyingthe general place as its place component 30.

The relevancy tool 36 is operable to determine a relevancy measure of anevent 18 with respect to a query 26. In some implementations, therelevancy of an event 18 with respect to a query 26 can be based on acomparison of the content 24 associated with the event 18 to the searchcomponent 32 of the query 26. For example, a numerical measure ofrelevancy can be determined based on this comparison.

The user data tool 38 is operable to read from or write to the user data14. In some implementations, the user data tool 38 can provide missingvalues to an input from a user 12 to complete a query 26. For example,if the user 12 specifies a search component 32, but not a time component28 or a place component 30, the user data tool 38 may provide defaultdata for a time component 28 and a place component 30 based oninformation in the user data 14. In some implementations, the defaultvalue for the place component 30 is the user's geographic location.

The event tool 40 is operable to read from or write to the event data16. In some implementations, the event tool 40 can operate as an eventcrawler. That is, the event tool 40 can be operable to examineelectronic documents on a network, determine whether the documentsdescribe one or more events 18, and if so, record the events 18 in theevent data 16. In some implementations, such documents are written in astructured language. In some implementations, for example, the eventtool 40 can determine time information 20 and/or place information 22 ofan event 18 based on the structured extensible markup language (“XML”)in a document describing the event 18.

In general, however, there is no requirement that a document beexpressed in a particular format or language. In particular, the webcrawler can identify events 18 described in plain text documents.

In some implementations, the event tool 40 is configured to receivedescriptions of events from previously-identified event feeds. Forexample, syndication sources may provide streams of events 18 via thereally simple syndication (“RSS”) protocol. In this case, the event tool40 can be operable to determine the time information 20, the placeinformation 22, and the content 24 for events 18 described in the feed.

In some implementations, the event tool 40 is configured to includeuser-specified events 18 in the event data 16. For example, if the user12 maintains a personal calendar on the event search system 10 orelsewhere, the user 12 may allow some or all of the events recorded onthe calendar to be searchable by some or all of the other users 12 ofthe event search system 10.

The query generator tool 42 is operable to generate a query 26 for theuser 12. In some implementations, the query generator tool 42 generatesa query 26 with a place component 30 based on the geographic location ofthe user 12. For example, the user 12 may use the query generator tool42 if the user 12 is curious as to what events 18 are occurring in hisgeographic vicinity. In some implementations, the search component 32 ofthe query 26 is based on search components 32 of queries from the user12 or other users 12. For example, the query generator tool 42 cangenerate a search component 32 based on popular search components 32from other users 12.

In some implementations, the search component 32 of the query 26 isgenerated based on the habits of the user 12. The habits of the user 12may be recorded in the user data 14. For example, the questionspertinent to the user's habits may be submitted to the user 12 registerswith the event search system 10, or from time to time afterregistration. The habits of the user may also be inferred by the user'sprevious use of the event search system 10. For example, a searchcomponent 32 may be generated based on the user's previously-suppliedsearch components, based on the events 18 previously viewed by the user12, etc.

In some implementations, the query generator tool 42 is operable toautomatically and periodically generate queries 26 based on a specifiedsearch component 32 of the user 12. For example, new queries 26 with thespecified search component 32 may be generated hourly, daily, weekly,etc. In some implementations, the time interval in the time component 28of the periodically generated queries is equal to the period with whichthe queries 26 are generated. For example, weekly-generated queries 26search for events occurring during that week. Thus, if a user 12 has apersistent interest in events 18 pertaining to patents, the user 12 mayarrange for periodically generated queries 26, each with the searchcomponent “patents.” The search component 32 may be saved, for example,in the user data 14.

The display tool 44 is operable to display output of the event searchsystem 10 to the various users 12. For example, such output may includesearch results based on user-supplied or system-generated queries 26. Insome implementations, the output is formatted consistently with apersonal calendar maintained by a user. In some implementations, theoutput is delivered to the user 12 via an electronic communication, suchas via a web page, e-mail, etc.

FIG. 4 is a flowchart for populating the event data 14. First, an eventdescription is identified (step 45). For example, the event descriptioncan be received by the event tool 40. In some implementations, the eventdescription is received from a web crawler, an external syndicationsource (for example, an RSS feed), a user 12, or any combination of thethese. Event descriptions may be identified from other sources. In someimplementations, the event description is formatted as structured XML.

Next, time information 28, place information 30, and content 32 aredetermined from the event description (step 46). For example, the eventtool 40 can determine the time information 28, the place information 30,and the content 32 from the event description. The time information 28,place information 30, and content 32 are then recorded (step 47). Forexample, the time information 28, place information 30, and content 32can be recorded as an event 18 in the event data 16. The process can berepeated for a plurality of events that are identified for processing.

Optionally, each event 18 recorded in step 47 may be automaticallycompared with one or more queries 26 (step 48). For example, each event18 may be compared with a saved search component 28 specified by a user12. In some implementations, comparing the event 18 with the query 26 orthe search component 28 includes determining a relevancy of the event 18with respect to the search component 28. The event 18 may beautomatically displayed to the user 12 (step 49). In someimplementations, the event 18 is displayed to a user 12 if the relevancyof the event 18 with respect to the user's saved search component 28 isabove a pre-determined threshold.

FIG. 5 is a flowchart for identifying which events from a collection ofevents satisfy a query 26. For example, the event data 14 may describe acollection of events 18. First, a query 26 is identified (step 50). Insome implementations, the query 26 is received by the query tool 34.Based on the query 26, partitions of the time interval by the timeincrement are identified (step 52). If no time increment was specifiedin the query 26, the entire time interval is treated as a singlepartition. In some implementations, the query tool 34 can be used toidentify the partitions.

From the collection of events, events which occur at or near the placespecified by the place component 30 of the query 26 are identified (step53). In some implementations, the event tool 40 can be used to identifysuch events 18. The events specified in step 53 are collectivelyreferred to as the localized collection of events, and step 53 isreferred to as localizing the collection of events.

For each time partition, events from the localized collection areassociated with the time partition (step 54). In some implementations,an event is associated with a time partition if the event's start timeoccurs during the partition. In some implementations, an event isassociated with a partition if any part of the event occurs during thepartition. In some implementations, events 18 occurring during a giventime partition can be identified by the event tool 40. For example, theevent tool 40 can identify such events based on the time component 28 ofthe query 26.

A partition is selected (step 56). For example, the partition may beselected by the query tool 34. For the events associated with theselected partition in step 54, a relevancy of each event to the receivedquery 26 is optionally determined (step 58). For example, the relevancymay be determined by the relevancy tool 36. In some examples, therelevancy of each event to the search component 32 of the query 26 isdetermined.

Based on the relevancy determination of step 58, one or more (e.g.several) events are selected to be displayed (step 60). In someimplementations, the events may be selected by the relevancy tool 36.For example, the events may be ranked according to their relevancy, anda pre-determined number of the highest-ranked events may be selected tobe displayed. In another example, all events above a pre-determinedrelevancy threshold are selected to be displayed. Other ways ofselecting events are possible.

If there are other partitions for which no events have yet been selectedto be displayed, steps 56-60 are repeated for those partitions.Eventually, the events selected to be displayed in step 60 are displayedfor each partition (step 62). For example, the events can be displayedby the display tool 44.

The above steps can be performed in other orders. For example, eventsmay be associated with a time partition prior to being localized; i.e.,the order of steps 53 and 54 may be reversed. Still other orders ofperforming the steps above are possible.

FIG. 6A is an exemplary set of event data 14. In this example, supposethe event data 14 contains six events 18 (a walk for charity, a pokertournament, a walking tour of Central Park, and a walking tour of Balboapark, a patent law seminar, and a jury duty recovery group), with timeinformation 20, place information 22, and content 24 as shown in FIG.6A. If an exemplary search query 26 with time component 28 indicatingthe time interval Jan. 1, 2006 to Jan. 5, 2006, place component 30indicating New York, N.Y., and a search component 32 consisting of theword “walk,” then the event search system 10 would display two events:the walk for charity and the central park walking tour.

FIG. 6B shows exemplary non-partitioned output 63 from the event searchsystem 10. This output 63 is presented as a list. FIG. 6C showsexemplary output from the event search system 10 partitioned by day.This output 63 shows events 18 in partitions corresponding to the dayson which the events 18 occur.

Note that, although the phrases “New York, N.Y.” and “Walker” appear inthe content 24 of the poker tournament event 18, this event 18 is notdisplayed among the search results, because its place information 22(Las Vegas) is not at or near the place component 30 (New York) of thequery 26. Conversely, note that the “walk for charity” at the BrooklynBridge appears among the search results, despite the textualdissimilarity of “Brooklyn Bridge” with “New York.” Finally, note thatthe jury duty recovery group event 18 was not included in the searchresults, despite occurring in the proper place, and the appearance of“walk” in its content 24, because it occurs at a time that is outsidethe time interval specified in the time component 28 of the query 26.

FIGS. 7A-D are screenshots of output from an event exemplary searchsystem 10, showing exemplary events 18 from a non-partitioned timeinterval of three days (FIG. 7A), events 18 from a given day partitionedinto hours (FIG. 7B), events 18 from a given week partitioned into daysand further partitioned into hours (FIG. 7C), and events 18 from a givenmonth partitioned into days (FIG. 7D). In some implementations, theoutput is provided by the display tool 44. Each screenshot may includefeatures such as a search component field 64, a place component field66, a time component field 68, a search button 70, an “I'm feelingbored” button 72, a navigation menu 74, a display menu 76, and a displayarea 78.

The search component, time component, and place component fields 64-68are text entry field, where a user 12 can specify values for the searchcomponent 32, time component 28, and place component 30, respectively,of a query 26. The search button 70 can be used to submit a query 26whose components 28-32 are equal to the values in the fields 64-68 tothe event search system 10. In some implementations, the values in thefields 64-68 are passed to the query tool 34 when the search button 70is activated.

The “I'm feeling bored” button 72 can be used to generate a query 26 andsubmit the query 26 to the event search system 10. The “I'm feelingbored” button 72 does not require any values to be entered in any of thefields 64-68. When the “I'm feeling bored” button 72 is activated, aquery 26 is automatically generated based on, e.g., past queries orrandomly generated and submitted to the event search system 10. In someimplementations, activating the “I'm feeling bored” button 72 calls thequery generator tool 42.

The navigation menu 74 includes controls for displaying events 18besides the ones currently in view. In some implementations, thenavigation menu 74 includes controls for selecting adjacent timeintervals for displaying events 18. For example, the navigation menu 74may include controls for displaying events 18 that occur during the nextor previous day (see FIG. 7B), for displaying events 18 that occurduring the next or previous week (see FIG. 7C), or for displaying events18 that occur during the next or previous month (see FIG. 7D). In someimplementations, the navigation menu 74 calls the query tool 34,providing a new query 26 specifying the requested time interval.

The display menu 76 includes controls for adjusting the time interval ortime increment(s) within which events 18 are displayed. In someimplementations, the display menu 76 includes controls for adjusting thetime interval to be a month, a week, or a day. In some implementations,the display menu 76 includes a control to display the events in the timeinterval without partitioning the time interval; i.e., as a list. Insome implementations, the controls in the display menu 76 call the querytool 34, providing the query tool 34 with a new time interval for apreviously-submitted query 26.

The display area 78 is an area where events 18 are displayed. In someimplementations, the display area 78 coincides with output from acomputer program; i.e., as an overlay. In some examples, the displayarea 78 coincides with a personal calendar maintained by the user 12viewing the events 18.

FIG. 8 is a block diagram of a computing device 80 that may be used toimplement the event search system 10, as either a client or as a serveror plurality of servers. Computing device 80 is intended to representvarious forms of digital computers, such as laptops, desktops,workstations, personal digital assistants, servers, blade servers,mainframes, and other appropriate computers. The components shown here,their connections and relationships, and their functions, are meant tobe exemplary only, and are not meant to limit implementations of theinventions described and/or claimed in this document.

Computing device 80 includes a processor 82, memory 84, a storage device86, a high-speed interface 88 connecting to memory 84 and high-speedexpansion ports 90, and a low-speed interface 92 connecting to low-speedbus 94 and storage device 86. Each of the components 82, 84, 86, 88, 90,and 92, are interconnected using various busses, and may be mounted on acommon motherboard or in other manners as appropriate. The processor 82can process instructions for execution within the computing device 80,including but not limited to instructions stored in the memory 84 or onthe storage device 86 to display graphical information for a GUI on anexternal input/output device, such as display 96 coupled to high-speedinterface 88. In other implementations, multiple processors and/ormultiple buses may be used, as appropriate, along with multiple memoriesand types of memory. Also, multiple computing devices 80 may beconnected, with each device providing portions of the necessaryoperations (e.g., as a server bank, a group of blade servers, or amulti-processor system).

The memory 84 stores information within the computing device 80. In oneimplementation, the memory 84 is a computer-readable medium. In oneimplementation, the memory 84 is a volatile memory unit or units. Inanother implementation, the memory 84 is a non-volatile memory unit orunits.

The storage device 86 is capable of providing mass storage for thecomputing device 80. In one implementation, the storage device 86 is acomputer-readable medium. In various different implementations, thestorage device 86 may be a floppy disk device, a hard disk device, anoptical disk device, or a tape device, a flash memory or other similarsolid state memory device, or an array of devices, including but notlimited to devices in a storage area network or other configurations. Inone implementation, a computer program product is tangibly embodied inan information carrier. The computer program product containsinstructions that, when executed, perform one or more methods, such asthose described above. The information carrier is a computer- ormachine-readable medium, such as the memory 84, the storage device 86,memory on processor 82, or a propagated signal.

The high-speed interface 88 manages bandwidth-intensive operations forthe computing device 80, while the low-speed interface 92 manages lowerbandwidth-intensive operations. Such allocation of duties is exemplaryonly. In one implementation, the high-speed interface 88 is coupled tomemory 84, display 96 (e.g., through a graphics processor oraccelerator), and to high-speed expansion ports 90, which may acceptvarious expansion cards (not shown). In the implementation, low-speedinterface 92 is coupled to storage device 86 and low-speed bus 94. Thelow-speed expansion port, which may include various communication ports(e.g., USB, Bluetooth, Ethernet, wireless Ethernet) may be coupled toone or more input/output devices, such as a keyboard, a pointing device,a scanner, or a networking device such as a switch or router, e.g.,through a network adapter.

The computing device 80 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as astandard server 130, or multiple times in a group of such servers. Itmay also be implemented as part of a rack server system 100. Inaddition, it may be implemented in a personal computer such as a laptopcomputer 102.

Various implementations of the event search system 10 can be realized indigital electronic circuitry, integrated circuitry, specially designedASICs (application specific integrated circuits), computer hardware,firmware, software, and/or combinations thereof. These variousimplementations can include implementation in one or more computerprograms that are executable and/or interpretable on a programmablesystem including but not limited to at least one programmable processor,which may be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms “machine-readable medium”“computer-readable medium” refers to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,Programmable Logic Devices (PLDs)) used to provide machine instructionsand/or data to a programmable processor, including but not limited to amachine-readable medium that receives machine instructions as amachine-readable signal. The term “machine-readable signal” refers toany signal used to provide machine instructions and/or data to aprogrammable processor.

To provide for interaction with a user, the event search system 10 canbe implemented on a computer having a display device (e.g., a CRT(cathode ray tube) or LCD (liquid crystal display) monitor) fordisplaying information to the user and a keyboard and a pointing device(e.g., a mouse or a trackball) by which the user can provide input tothe computer. Other kinds of devices can be used to provide forinteraction with a user as well; for example, feedback provided to theuser can be any form of sensory feedback (e.g., visual feedback,auditory feedback, or tactile feedback); and input from the user can bereceived in any form, including but not limited to acoustic, speech, ortactile input.

The event search system 10 can be implemented in a computing system thatincludes a back end component (e.g., as a data server), or that includesa middleware component (e.g., an application server), or that includes afront end component (e.g., a client computer having a graphical userinterface or a Web browser through which a user can interact with animplementation of the event search system 10), or any combination ofsuch back end, middleware, or front end components. The components ofthe system can be interconnected by any form or medium of digital datacommunication (e.g., a communication network). Examples of communicationnetworks include a local area network (“LAN”), a wide area network(“WAN”), and the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

Other embodiments are within the scope of the following claims.

1. A method comprising: identifying a query, the query including a timeinterval and a search component; determining a time increment associatedwith the time interval; partitioning, based on the time increment, thetime interval into partitions; for each partition, determining, based onthe query, a relevance of each event in a collection of events thatoccur at a time in the partition; and displaying a pre-determined numberof the relevant events.
 2. The method of claim 1, wherein determining atime increment includes determining a time increment based on the query.3. The method of claim 1, wherein determining the relevance of eachevent is based on the search component of the query.
 4. The method ofclaim 1, wherein the query also includes a place component thatdescribes a place, and for each partition, the collection of eventsincludes events that occur within a pre-determined relationship with theplace.
 5. The method of claim 4, in which the pre-determinedrelationship includes a geographical proximity.
 6. The method of claim1, wherein determining the relevance of an event includes determining anumerical relevance of the event.
 7. The method of claim 1, furthercomprising generating the query.
 8. The method of claim 7, wherein thequery is randomly generated.
 9. The method of claim 8, wherein thesearch component of the query is randomly generated.
 10. The method ofclaim 7, wherein the query is generated based on a property of a user.11. The method of claim 10, wherein the property includes aquery-history of the user.
 12. The method of claim 11, wherein thesearch component of the query is generated based on the query-history ofthe user.
 13. The method of claim 7, wherein the search component of thequery is supplied by a user, and the time interval of the query isautomatically generated.
 14. The method of claim 13, further comprisingsuccessively generating two queries, each of which having the samesearch component supplied by the user.
 15. A method comprising:identifying an event described by an electronic document, whereinidentifying the event includes identifying a time or times at which theevent occurs, a place or places at which the event occurs, and contentfrom the electronic document, the content describing the event; andrecording the time or times at which the event occurs, the place orplaces at which the event occurs, and the content describing the eventon a computer readable medium.
 16. The method of claim 15, furthercomprising identifying the electronic document by using a crawler on acomputer network.
 17. The method of claim 16, in which the computernetwork includes a world wide web.
 18. The method of claim 15, in whichthe electronic document is expressed in a structured language, and theevent is identified using a structure of the language.
 19. The method ofclaim 18, in which the structured language includes extensible markuplanguage, and the event is identified using tags in the structuredlanguage.
 20. The method of claim 15, in which the electronic documentdescribes a calendar, and the event includes an event in the calendar.21. The method of claim 15, in which the event is identified from asyndicated feed.
 22. The method of claim 21, in which the syndicatedfeed includes an RSS feed.
 23. The method of claim 16 further comprisingdetermining a relevance of the event with respect to a pre-determinedquery, the query being determined prior to identifying the event.
 24. Amethod comprising: identifying a query, the query including a timeinterval and a search component; identifying one or more partitionsbased on the time interval; for each partition, determining events basedon the search component; and displaying the events for each partition.25. The method of claim 24, in which the query also includes a placecomponent that describes a place, and for each partition, the collectionof events includes events that occur within a pre-determinedrelationship with the place.
 26. The method of claim 25, in which thepre-determined relationship includes a geographical proximity.
 27. Themethod of claim 24, further comprising generating the query.
 28. Themethod of claim 27, in which the query is randomly generated.
 29. Themethod of claim 28, wherein the search component of the query israndomly generated.
 30. The method of claim 27, in which the query isgenerated based on a property of a user.
 31. The method of claim 30,wherein the property includes a query-history of the user.
 32. Themethod of claim 31, wherein the search component of the query isgenerated based on the query-history of the user.
 33. The method ofclaim 27, wherein the search component of the query is supplied by auser, and the time interval of the query is automatically generated. 34.The method of claim 33, further comprising successively generating twoqueries, each of which having the same search component supplied by theuser.
 35. A system comprising: means for identifying a query, the queryincluding a time interval and a search component; means for determininga time increment associated with the time interval; means forpartitioning, based on the time increment, the time interval intopartitions; means for determining, for each partition, based on thesearch component, a relevance of each event in a collection of eventsthat occur at a time in the partition; and means for displaying apre-determined number of the relevant events.
 36. The system of claim35, wherein the means for determining a time increment includes meansfor determining a time increment based on the query.
 37. The system ofclaim 35, wherein the means for determining the relevance of each eventis configured to determine the relevance of each event based on thesearch component of the query.
 38. The system of claim 35, wherein thequery also includes a place component that describes a place, and foreach partition, the collection of events includes events that occurwithin a pre-determined relationship with the place.
 39. The system ofclaim 38, in which the pre-determined relationship includes ageographical proximity.
 40. The system of claim 35, wherein the meansfor determining the relevance of an event includes means for determininga numerical relevance of the event.
 41. The system of claim 35, furthercomprising means for generating the query.
 42. The system of claim 41,wherein the means for generating the query includes means for randomlygenerating the query.
 43. The system of claim 41, wherein the means forgenerating the query includes means for generating the query based on aproperty of a user.
 44. The system of claim 43, wherein the means forgenerating the query includes means for generating the query based on aquery-history of the user.
 45. The system of claim 43, wherein the meansfor generating the query includes means for generating the searchcomponent of the query based on the query-history of the user.
 46. Thesystem of claim 41, wherein the search component of the query issupplied by a user, and the means for generating the query includesmeans for generating the time interval of the query.
 47. A systemcomprising: means for identifying an event described by an electronicdocument, wherein identifying the event includes identifying a time ortimes at which the event occurs, a place or places at which the eventoccurs, and content from the electronic document, the content describingthe event; and means for recording the time or times at which the eventoccurs, the place or places at which the event occurs, and the contentdescribing the event on a computer readable medium.
 48. The system ofclaim 47, in which the means for identifying an event includes a crawlerconnected to a computer network.
 49. The system of claim 48, in whichthe computer network includes the world wide web.
 50. The system ofclaim 47, in which the electronic document is expressed in a structuredlanguage, and the event is identified using a structure of the language.51. The system of claim 50, in which the structured language includesextensible markup language, and the means for identifying the eventincludes means for identifying the event using tags in the structuredlanguage.
 52. The system of claim 47, in which the electronic documentdescribes a calendar, and the means for identifying an event includesmeans for identifying an event in the calendar.
 53. The system of claim47, in which the means for identifying an event includes means foridentifying an event described in a syndicated feed.
 54. The system ofclaim 53, in which the means for identifying an event described in asyndicated feed includes means for identifying an event in an RSS feed.55. The system of claim 48 further comprising means for determining arelevance of the event with respect to a pre-determined query, the querybeing determined prior to identifying the event.
 56. A computer-readablemedium bearing instructions that, when executed, cause a computer to:identify a query, the query including a time interval and a searchcomponent; determine a time increment associated with the time interval;partition, based on the time increment, the time interval intopartitions; determine, for each partition, based on the searchcomponent, a relevance of each event in a collection of events thatoccur at a time in the partition; and display a pre-determined number ofthe relevant events.
 57. The computer-readable medium of claim 56,wherein the instructions for determining a time increment includesinstructions for determining a time increment based on the query. 58.The computer-readable medium of claim 56, wherein the instructions fordetermining the relevance of each event includes instructions todetermine the relevance of each event based on the search component ofthe query.
 59. The computer-readable medium of claim 56, wherein thequery also includes a place component that describes a place, and foreach partition, the collection of events includes events that occurwithin a pre-determined relationship with the place.
 60. Thecomputer-readable medium of claim 59, in which the pre-determinedrelationship includes a geographical proximity.
 61. Thecomputer-readable medium of claim 56, wherein the instructions fordetermining the relevance of an event includes instructions fordetermining a numerical relevance of the event.
 62. Thecomputer-readable medium of claim 56, further comprising instructionsthat, when executed, cause the computer to generate the query.
 63. Thecomputer-readable medium of claim 62, wherein the instructions forgenerating the query include instructions for randomly generating thequery.
 64. The computer-readable medium of claim 62, wherein theinstructions for generating the query include instructions forgenerating the query based on a property of a user.
 65. Thecomputer-readable medium of claim 64, wherein the instructions forgenerating the query include instructions for generating the query basedon a query-history of the user.
 66. The computer-readable medium ofclaim 64, wherein the instructions for generating the query includeinstructions for generating the search component of the query based onthe query-history of the user.
 67. The computer-readable medium of claim62, wherein the search component of the query is supplied by a user, andthe instructions for generating the query include instructions forgenerating the time interval of the query.
 68. A first computer-readablemedium bearing instructions that, when executed, cause a computer to:identify an event described by an electronic document, whereinidentifying the event includes identifying a time or times at which theevent occurs, a place or places at which the event occurs, and contentfrom the electronic document, the content describing the event; andrecord the time or times at which the event occurs, the place or placesat which the event occurs, and the content describing the event on asecond computer-readable medium.
 69. The first computer-readable mediumof claim 68, in which the instructions for identifying an event includea crawler connected to a computer network.
 70. The computer-readablemedium of claim 69, in which the computer network includes the worldwide web.
 71. The computer-readable medium of claim 68, in which theelectronic document is expressed in a structured language, and the eventis identified using a structure of the language.
 72. Thecomputer-readable medium of claim 71, in which the structured languageincludes extensible markup language, and the instructions foridentifying the event includes instructions for identifying the eventusing tags in the structured language.
 73. The computer-readable mediumof claim 68, in which the electronic document describes a calendar, andthe instructions for identifying an event include instructions foridentifying an event in the calendar.
 74. The computer-readable mediumof claim 68, in which the instructions for identifying an event includeinstructions for identifying an event described in a syndicated feed.75. The computer-readable medium of claim 74, in which the instructionsfor identifying an event described in a syndicated feed includesinstructions for identifying an event in an RSS feed.
 76. Thecomputer-readable medium of claim 69, further comprising instructionsthat, when executed, cause the computer to determine a relevance of theevent with respect to a pre-determined query, the query being determinedprior to identifying the event.